An Approach to the Development of Inference Engine for Distributed System for Fault Diagnosis

The reliable and fault tolerant computers are key to the success to aerospace, and communication industries. Designing a reliable digital system, and detecting and repairing the faults are challenging tasks in order for the digital system to operate without failures for a given period of time. The paper presents a new and systematic software engineering approach of performing fault diagnosis parallel and distributed computing. The purpose of the paper would be to demonstrate a method to build a fault diagnosis for a parallel and distributed computing. The paper chooses a model posed a tremendous challenge to the user for fault analysis. The model is the classic PMC model that happens to be a parallel and distributed computing. The paper would also show a method for building an optimal inference engine by obtaining sub graphs that also preserve the necessary and sufficient conditions of the model. Coin words: Parallel and Distributed Computing, Artificial Intelligence.